Vedad Misirlic
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Vedad Misirlic has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Elisabeth Lex
Graz University of Technology, Graz, Austria
2 shared publications - Gerald Stieglbauer
AVL List GmbH, Graz, Austria
1 shared publication - Gregor Mayr
Graz University of Technology, Graz, Austria
1 shared publication - Kevin Innerebner
Graz University of Technology, Graz, Austria
1 shared publication
Latest Publications
- Open Access
- 6 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 9481-9483
Adapting Code LLMs to Domain-specific Languages via Synthethic Instruction Generation and Reinforcement Learning with AI Feedback in Low-resource Settings
- 6 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 9481-9483
Open AccessAdapting Code LLMs to Domain-specific Languages via Synthethic Instruction Generation and Reinforcement Learning with AI Feedback in Low-resource Settings
- Open Access
- 24 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 1-13
Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD
Short-form video platforms use recommender systems to maximize engagement through highly efficient personalized recommendations. However, the impact of these recommendations on users with ADHD compared to users without ADHD remains underexplored. Through this study, we introduce and operationalize the Engagement Trap, illustrating how recommender systems, while successfully optimizing for engagement, disproportionately disadvantage users with ADHD. This stratified study of 302 participants, recruited via the online platform Prolific, compares experiences between participants with and without ADHD. Our results show that while recommendations are perceived as relevant across groups, participants with ADHD report significantly higher levels of time blindness, post-usage regret, and emotional distress when consuming recommendations. Moreover, we collect feedback for several proof-of-concept, theoretical design interventions for neuro-inclusive design principles. These findings provide quantitative evidence of systemic differences in engagement-optimized recommender systems and highlight the unbalanced negative effects and interactions these systems create for participants with ADHD. We argue for neurodiversity-aware, human-centered design approaches that mitigate such algorithmic harms and support more equitable experiences.
- 24 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 1-13
Open AccessQuantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD
Short-form video platforms use recommender systems to maximize engagement through highly efficient personalized recommendations. However, the impact of these recommendations on users with ADHD compared to users without ADHD remains underexplored. Through this study, we introduce and operationalize the Engagement Trap, illustrating how recommender systems, while successfully optimizing for engagement, disproportionately disadvantage users with ADHD. This stratified study of 302 participants, recruited via the online platform Prolific, compares experiences between participants with and without ADHD. Our results show that while recommendations are perceived as relevant across groups, participants with ADHD report significantly higher levels of time blindness, post-usage regret, and emotional distress when consuming recommendations. Moreover, we collect feedback for several proof-of-concept, theoretical design interventions for neuro-inclusive design principles. These findings provide quantitative evidence of systemic differences in engagement-optimized recommender systems and highlight the unbalanced negative effects and interactions these systems create for participants with ADHD. We argue for neurodiversity-aware, human-centered design approaches that mitigate such algorithmic harms and support more equitable experiences.